Construction Of SERS Microfluidic Chip Substrate And Its Application In Detection Of Multiple Tumor Markers

The early diagnosis of cancer is crucial to reduce the mortality of cancer.One of the important and effective ways is to detect the expression level of tumor biomarkers.Because the content of tumor biomarkers in the early stage of cancer is often low,and a tumor biomarker is often associated with multiple tumors.Therefore,it is of great significance that a tumor biomarker detection platform with high detection sensitivity,high throughput,and low cost is used for the early diagnosis of cancer.This dissertation mainly studied the construction of SERS microfluidic chip substrate and its application in the detection of multiple tumor biomarkers.By integrating SERS detection technology,microfluidic chip technology,and tumor biomarker immunodetection technology in one,this paper designed and constructed a multiplex detection platform based on SERS microfluidic chip substrate and applied it to the detection of human whole blood samples.All of these provided an effective solution for early clinical diagnosis of cancer.The main innovative research results are as follows:?1?A SERS microfluidic chip for simultaneous detection of multiple tumor biomarkers was proposed.The SERS substrate of the microfluidic chip was obtained by layer assembly using an electrostatic adsorption method.The tumor biomarkers in serum were detected using the“sandwich”immunoassay strategy and the combined detection of breast cancer markers CA153,CA125,and CEA in serum was performed with a spatial coding method.The detection limits were 0.01 U/mL and 0.01 U/mL and 1 pg/mL,respectively,which were 2-3orders of magnitude lower than current commercial ELISA kits.?2?A SERS microfluidic chip substrate with SERS"hot-planes"properties was designed and applied to the detection of tumor biomarkers.In the experiment,an ordered array substrate with a high degree of homogeneity was prepared by means of inverse molding using AAO as a template.This substrate with SERS“hot-planes”properties was prepared by vacuum sputtering of silver and modification of silver nanoparticles using DNA as a bridge.The SERS-active substrate was then embedded into the microfluidic chip channel by bonding to obtain a SERS microfluidic chip substrate.The limit of detection of this proposed microfluidic biosensor was as low as 10^-5 U/mL for breast cancer tumor biomarker CA153 in serum.This biosensor had the advantages of good repeatability,high detection sensitivity,easy operation and low cost,and provided an efficient strategy for the early diagnosis of cancer.?3?Explore the application of machine learning combined with SERS spectroscopy in the identification of breast cancer cells.In experiments,the SERS spectra of breast cancer cells MDA-MB-231 and normal breast epithelial cells MCF-10A were detected by using label-free method and microfluidic chip SERS-active substrate with SERS"hot-planes"properties.Afterwards,machine learning was used for data processing and data analysis,and machine learning models were then trained.Finally,Raman spectroscopy was used to automatically determine cell type.The program is simple in operation,and fully utilizes the rich biochemical information and fingerprint characteristics contained in Raman spectroscopy.With the help of powerful data analysis capabilities of machine learning,it ultimately achieves 100%accuracy in the identification of breast cancer cells.The program reveals the enormous research value and application prospects of machine learning in the fields of biophotonics,cell classification,and biological analysis.